NDLI: Comparing color edge detection and segmentation methods

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Comparing color edge detection and segmentation methods

Content Provider	IEEE Xplore Digital Library
Author	Allen, J.T. Huntsberger, T.
Copyright Year	1989
Description	Author affiliation: Dept. of Comput. Sci., Furman Univ., Greenville, SC, USA (Allen, J.T.)
Abstract	The authors report the results of a controlled comparative study of four proposed methods for extracting boundaries in static images using color information. The first two techniques are, more properly speaking, edge-detection methods. These include the adaptation of the Hueckel operator to color images by R. Nevatia (1977) and the DOOG (difference of offset Gaussians) operator proposed by R. Young (1985, 1986). The latter two methods are examples of region-based segmentation. These include the adaptation of R. Ohlander et al. (1978), region splitting by Y. Ohta et al. (1980), and the fuzzy c-means segmentation and edge-detection methods of T.L. Huntsberger et al. (1985). The methods are compared using both simulated, controlled images as well as a variety of natural scene images. Images with various levels of randomly additive noise provide some indication of the degradation of performance of these methods under noisy conditions.
Starting Page	722
Ending Page	728
File Size	869236
Page Count	7
File Format	PDF
DOI	10.1109/SECON.1989.132495
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-04-09
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Gaussian processes Testing Histograms Computer science Least squares approximation Displays Biological system modeling Machine vision Lighting
Content Type	Text
Resource Type	Article

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